@techreport{oai:ipsj.ixsq.nii.ac.jp:00082928,
 author = {山田, 一郎 and 宮崎, 勝 and 住吉, 英樹 and 古宮, 弘智 and 田中, 英輝 and Ichiro, Yamada and Masaru, Miyazaki and Hideki, Sumiyoshi and Hironori, Furumiya and Hideki, Tanaka},
 issue = {12},
 month = {Jul},
 note = {テレビ番組を配信するオンデマンドサービスでは、ユーザへの番組推薦機能が重要となる。そこで本稿では、テレビの電子番組表(EPG)に含まれる番組概要文を利用して効果的な関連番組を推薦するための番組類似性評価手法を提案する。提案手法では、番組概要文に含まれる単語をノードとし、Webから取り出した単語間の関係（因果関係や上位下位関係など）で各ノードを結合したグラフ構造を生成する。このグラフ構造のノード間の到達可能性をランダムウォークにより評価する事によって、番組間の類似性を評価する。実験ではNHKオンデマンドで実際に提示された関連番組を対象とした類似性評価を行い、提案手法の結果は従来手法と比較して人手による類似性評価結果に近いことを示す。, This paper presents a novel method of calculating similarity between TV programs by using summaries as a part of Electronic Program Guide (EPG). Most previous methods used statistics such as tf-idf based cosine measure of word vectors, whose words are appeared in the summaries. However these approaches were not effective for calculating similarity between TV programs because broadcast summaries are too short to obtain reliable statistics. Our method generates a graph structures whose vertexes are TV programs and words. These words are connected by word relations which are extracted from Web automatically. Similarity between two TV programs is calculated based on the relativeness of two TV program's vertexes in the graph structure by using a random walk algorithm. Through experiments, our method showed effectiveness of calculating similarities between two TV programs compared with the baseline approaches.},
 title = {ランダムウォークを利用した番組類似性評価},
 year = {2012}
}